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Multi-layer Data to Improve Diagnosis, Predict Therapy Resistance and Suggest Targeted Therapies in HGSOC (DECIDER)

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ClinicalTrials.gov Identifier: NCT04846933
Recruitment Status : Recruiting
First Posted : April 15, 2021
Last Update Posted : June 18, 2023
Sponsor:
Collaborator:
University of Helsinki
Information provided by (Responsible Party):
Turku University Hospital

Tracking Information
First Submitted Date April 12, 2021
First Posted Date April 15, 2021
Last Update Posted Date June 18, 2023
Actual Study Start Date February 1, 2012
Estimated Primary Completion Date December 2027   (Final data collection date for primary outcome measure)
Current Primary Outcome Measures
 (submitted: April 12, 2021)
  • Successful clinical translation [ Time Frame: 5 years ]
    The magnitude of successful clinical translation is measured by the number of times project-derived personalized medicine has impacted patients care by application of novel and existing biomarkers and therapies.
  • Successful prediction of patient outcome with AI methods [ Time Frame: 5 years ]
    Proportion of patients whose disease outcome (PFS, OS) is predicted correctly with digital histopathology images, genomic data and routine laboratory values
Original Primary Outcome Measures Same as current
Change History
Current Secondary Outcome Measures
 (submitted: April 12, 2021)
  • Successful validation of potentially druggable genetic alterations [ Time Frame: 5 years ]
    Number of potentially druggable genetic alterations found and validated with in-vitro methods
  • Successful prediction of genomic features from tumor histology [ Time Frame: 5 years ]
    Number of genomic features that can be successfully recognized from tumor histology
  • Prediction of primary treatment response from tumor histology using H&E stained whole slide images and AI-based methods [ Time Frame: 5 years ]
    Number of patients whose outcome (primary therapy outcome, PFS) is predicted correctly
  • Establishment of an updated version of Chemoresponse score (CRS) for measuring histological effect in tumor tissue after chemotherapy [ Time Frame: 5 years ]
    Predictive power of the updated CRS at interval surgery is compared with traditional CRS
Original Secondary Outcome Measures Same as current
Current Other Pre-specified Outcome Measures Not Provided
Original Other Pre-specified Outcome Measures Not Provided
 
Descriptive Information
Brief Title Multi-layer Data to Improve Diagnosis, Predict Therapy Resistance and Suggest Targeted Therapies in HGSOC
Official Title Integration of Multiple Data Levels to Improve Diagnosis, Predict Treatment Response and Suggest Targets to Overcome Therapy Resistance in High-grade Serous Ovarian Cancer
Brief Summary

Chemotherapy resistance is the greatest contributor to mortality in advanced cancers and severe challenges remain in finding effective treatment modalities to cancer patients with metastasized and relapsed disease. High-grade serous ovarian cancer (HGSOC) is typically diagnosed at a stage where the disease is already widely spread to the abdomen and current standard of practice treatment consists of surgery followed by platinum-taxane based chemotherapy and maintenance therapy. While 90% of HGSOC patients show no clinically detectable signs of cancer after surgery and chemotherapy, only 43% of the patients are alive five years after diagnosis because of chemoresistant cancer.

This prospective, observational trial focuses on revealing major mechanisms causing chemoresistance in HGSOG patients and derive personalized treatment regimens for chemotherapy resistant HGSOC patients. The investigators recruit newly diagnosed advanced stage HGSOC patients who are then thoroughly followed during their cancer treatment. Longitudinal sampling includes digitalized H&E stained histology slides mainly collected during routine diagnostics, fresh tumor & ascites samples for next-generation sequencing/proteomics (WGS, RNA-seq, DNA-methylation, ChIP-seq, mass cytometry, etc.) and ex vivo experiments, plasma samples for circulating tumor DNA (ctDNA) analyses. Broad range of clinical parameters such as laboratory and radiologic parameters (e.g., FDG PET/CT), given cancer treatments and their outcomes are collected.

The general objective is to establish a clinically useful precision oncology approach based on multi-level data collected in longitudinal setting, and translate the most potent and validated discoveries into clinical use. DECIDER project will produce AI-powered diagnostic tools, cutting-edge software platforms for clinical decision-making, novel data analysis & integration methods, and high-throughput ex vivo drug screening approaches.

Detailed Description

Specific aims include:

  • Develop tools and methods for personalized medicine approaches to cancer patients.
  • Develop open-source visualization and interpretation software that facilitate clinical decision making via data integration and interpretation of multilevel data from cancer patients.
  • Rapidly identify HGSOC patients who are likely to respond poorly to current therapies combining information on digitalized histopathology samples, genomic and clinical data with AI methods.
  • Deploy validated personalized medicine treatment options using longitudinal measurement and ex vivo cultures from cancer patients in clinical care.
Study Type Observational
Study Design Observational Model: Cohort
Time Perspective: Prospective
Target Follow-Up Duration Not Provided
Biospecimen Retention:   Samples With DNA
Description:
Tumor tissue (Fresh frozen tissue, FFPE), Whole blood samples, plasma, white cells
Sampling Method Non-Probability Sample
Study Population High grade serous ovarian cancer patients diagnosed at theTurku University Central Hospital who give their informed consent
Condition
  • High Grade Ovarian Serous Adenocarcinoma
  • High Grade Serous Carcinoma
Intervention
  • Genetic: WGS and RNA sequencing
  • Genetic: circulating tumor DNA (ctDNA)
  • Diagnostic Test: FDG PET/CT imaging
Study Groups/Cohorts
  • HGSOC patients treated with Neoadjuvant chemotherapy (NACT)

    Diagnostic laparoscopy followed with 3-4 cycles of platinum-taxane NACT and interval debulking surgery (IDS). Treatment response is monitored with FDG PET/CT. IDS is followed by standard adjuvant therapy (ESGO/ESMO + local guidelines).

    Digital H&E slides and WGS, RNAseq are obtained from performed surgeries including relapse operations/ascites drainages. Patients are followed with longitudinal ctDNA sampling.

    Interventions:
    • Genetic: WGS and RNA sequencing
    • Genetic: circulating tumor DNA (ctDNA)
    • Diagnostic Test: FDG PET/CT imaging
  • HGSOC patients treated with primary debulking surgery (PDS)
    PDS is followed by standard adjuvant therapy (ESGO/ESMO + local guidelines). Digital H&E slides and WGS, RNAseq obtained from PDS and possible relapse operations/ascites drainages when performed. Patients are followed with longitudinal ctDNA sampling.
    Interventions:
    • Genetic: WGS and RNA sequencing
    • Genetic: circulating tumor DNA (ctDNA)
Publications * Not Provided

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
Recruitment Information
Recruitment Status Recruiting
Estimated Enrollment
 (submitted: April 12, 2021)
200
Original Estimated Enrollment Same as current
Estimated Study Completion Date December 2029
Estimated Primary Completion Date December 2027   (Final data collection date for primary outcome measure)
Eligibility Criteria

Inclusion Criteria:

  • Patients with a suspected ovarian cancer diagnosis treated at the Turku University Hospital
  • Ability to understand and the willingness to sign a written informed consent document

Exclusion Criteria:

  • Age <18 years, too poor condition for active treatment (surgery, chemotherapy)
  • FDG PET/CT scan is not performed for patients with diabetes mellitus and poor glucose balance.
Sex/Gender
Sexes Eligible for Study: Female
Ages 18 Years and older   (Adult, Older Adult)
Accepts Healthy Volunteers No
Contacts
Contact: Johanna Hynninen +358 50 5383554 johanna.hynninen@utu.fi
Contact: Sampsa Hautaniemi +358503364765 sampsa.hautaniemi@helsinki.fi
Listed Location Countries Finland
Removed Location Countries  
 
Administrative Information
NCT Number NCT04846933
Other Study ID Numbers TO7/003/21
965193 ( Other Grant/Funding Number: EU HORIZON 2020 )
Has Data Monitoring Committee Yes
U.S. FDA-regulated Product
Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
IPD Sharing Statement Not Provided
Current Responsible Party Turku University Hospital
Original Responsible Party Same as current
Current Study Sponsor Turku University Hospital
Original Study Sponsor Same as current
Collaborators University of Helsinki
Investigators
Study Director: Sampsa Hautaniemi, DTech, Prof University of Helsinki
Principal Investigator: Johanna Hynninen, MD, PhD Turku University Hospital
PRS Account Turku University Hospital
Verification Date June 2023